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A multiepitopic theoretical fusion construct based on in-silico epitope screening of known vaccine candidates for protection against wide range of enterobacterial pathogens
Enterobacterial pathogens that have acquired antibiotic resistance genes are a leading cause of community and hospital acquired infections. In such a situation vaccination is considered as a better option to prevent such infections. In the current study reverse vaccinology approach has been used to...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7115567/ https://www.ncbi.nlm.nih.gov/pubmed/30769032 http://dx.doi.org/10.1016/j.humimm.2019.02.008 |
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author | Kumar, Ashutosh Harjai, Kusum Chhibber, Sanjay |
author_facet | Kumar, Ashutosh Harjai, Kusum Chhibber, Sanjay |
author_sort | Kumar, Ashutosh |
collection | PubMed |
description | Enterobacterial pathogens that have acquired antibiotic resistance genes are a leading cause of community and hospital acquired infections. In such a situation vaccination is considered as a better option to prevent such infections. In the current study reverse vaccinology approach has been used to select peptides from already known immunogenic proteins to design a chimeric construct. We selected Yersiniabactin receptor of Escherichia coli UMN026 and Flagellin of Stenotrophomonas maltophila. B-cell linear epitopes were predicted using Bepipred prediction tool. Peptide binding with reference sets of 27 alleles of MHC class I and class II was also analyzed. The predicted peptides-MHC complexes were further validated using simulation dynamics. The in-silico construction of chimera was done by restriction mapping and codon optimization. Chimera was evaluated using the immunoinformatic approach as done for the selected proteins. From the 673 amino acids of FyuA protein, a region from 1 to 492 was selected for containing more linear epitopes and the processing scores obtained were significant for MHC class I and class II binding. Similarly, from Flagellin, a region between 60 and 328 amino acids was selected and the peptides present in the selected region showed lower percentile ranks for binding with MHC molecules. The simulation studies validated the predictions of peptide-MHC complexes. The selected gene fragments accommodating maximum part of these peptides were used to design a chimaeric construct of 2454 bp. From the immunoinformatic analysis, the chimera was found to be more immunogenic in terms of increased number of B-cell and T-cell epitopes along with increased coverage of global populations with allelic variability. |
format | Online Article Text |
id | pubmed-7115567 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-71155672020-04-02 A multiepitopic theoretical fusion construct based on in-silico epitope screening of known vaccine candidates for protection against wide range of enterobacterial pathogens Kumar, Ashutosh Harjai, Kusum Chhibber, Sanjay Hum Immunol Article Enterobacterial pathogens that have acquired antibiotic resistance genes are a leading cause of community and hospital acquired infections. In such a situation vaccination is considered as a better option to prevent such infections. In the current study reverse vaccinology approach has been used to select peptides from already known immunogenic proteins to design a chimeric construct. We selected Yersiniabactin receptor of Escherichia coli UMN026 and Flagellin of Stenotrophomonas maltophila. B-cell linear epitopes were predicted using Bepipred prediction tool. Peptide binding with reference sets of 27 alleles of MHC class I and class II was also analyzed. The predicted peptides-MHC complexes were further validated using simulation dynamics. The in-silico construction of chimera was done by restriction mapping and codon optimization. Chimera was evaluated using the immunoinformatic approach as done for the selected proteins. From the 673 amino acids of FyuA protein, a region from 1 to 492 was selected for containing more linear epitopes and the processing scores obtained were significant for MHC class I and class II binding. Similarly, from Flagellin, a region between 60 and 328 amino acids was selected and the peptides present in the selected region showed lower percentile ranks for binding with MHC molecules. The simulation studies validated the predictions of peptide-MHC complexes. The selected gene fragments accommodating maximum part of these peptides were used to design a chimaeric construct of 2454 bp. From the immunoinformatic analysis, the chimera was found to be more immunogenic in terms of increased number of B-cell and T-cell epitopes along with increased coverage of global populations with allelic variability. American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. 2019-07 2019-02-12 /pmc/articles/PMC7115567/ /pubmed/30769032 http://dx.doi.org/10.1016/j.humimm.2019.02.008 Text en © 2019 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Kumar, Ashutosh Harjai, Kusum Chhibber, Sanjay A multiepitopic theoretical fusion construct based on in-silico epitope screening of known vaccine candidates for protection against wide range of enterobacterial pathogens |
title | A multiepitopic theoretical fusion construct based on in-silico epitope screening of known vaccine candidates for protection against wide range of enterobacterial pathogens |
title_full | A multiepitopic theoretical fusion construct based on in-silico epitope screening of known vaccine candidates for protection against wide range of enterobacterial pathogens |
title_fullStr | A multiepitopic theoretical fusion construct based on in-silico epitope screening of known vaccine candidates for protection against wide range of enterobacterial pathogens |
title_full_unstemmed | A multiepitopic theoretical fusion construct based on in-silico epitope screening of known vaccine candidates for protection against wide range of enterobacterial pathogens |
title_short | A multiepitopic theoretical fusion construct based on in-silico epitope screening of known vaccine candidates for protection against wide range of enterobacterial pathogens |
title_sort | multiepitopic theoretical fusion construct based on in-silico epitope screening of known vaccine candidates for protection against wide range of enterobacterial pathogens |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7115567/ https://www.ncbi.nlm.nih.gov/pubmed/30769032 http://dx.doi.org/10.1016/j.humimm.2019.02.008 |
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